Based on prior knowledge, we can analyze the relationship between the feature "fibr_ter_03" and the task of determining if the patient has chronic heart failure.

To analyze this relationship, we need to consider the possible values of the feature "fibr_ter_03" and how they correlate with the presence or absence of chronic heart failure.

Here's a possible analysis:

- If the feature value of "fibr_ter_03" is "no", it indicates that the patient did not receive fibrinolytic therapy by Celiasum 3m IU.
- If the feature value of "fibr_ter_03" is "yes", it indicates that the patient received fibrinolytic therapy by Celiasum 3m IU.

Now, we can create a dictionary to summarize the relationship between the feature "fibr_ter_03" and the target variable (presence or absence of chronic heart failure).

```json
{
	"no": ["no"], 
	"yes": ["yes"]
}
```

In this case, since the feature "fibr_ter_03" does not directly provide information about chronic heart failure, the presence or absence of chronic heart failure cannot be determined solely based on this feature. However, we can still include the possible values of the feature in the dictionary for completeness.